10585054
28997
Marc Boel
9967
Supervised Classification
19039
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(2)
8301336
Python_3.7.12. Sklearn_1.0.1. NumPy_1.19.5. SciPy_1.4.1.
n_jobs
null
19031
remainder
"drop"
19031
sparse_threshold
0.3
19031
transformer_weights
null
19031
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}]
19031
verbose
false
19031
verbose_feature_names_out
true
19031
add_indicator
false
19032
copy
true
19032
fill_value
null
19032
missing_values
NaN
19032
strategy
"most_frequent"
19032
verbose
0
19032
categories
"auto"
19033
drop
null
19033
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
19033
handle_unknown
"ignore"
19033
sparse
true
19033
memory
null
19039
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]
19039
verbose
false
19039
ccp_alpha
0.0
19040
criterion
"friedman_mse"
19040
init
null
19040
learning_rate
0.8706146447446743
19040
loss
"deviance"
19040
max_depth
3
19040
max_features
null
19040
max_leaf_nodes
1726
19040
min_impurity_decrease
0.0
19040
min_samples_leaf
38
19040
min_samples_split
2
19040
min_weight_fraction_leaf
0.0
19040
n_estimators
100
19040
n_iter_no_change
8
19040
random_state
24538
19040
subsample
1.0
19040
tol
0.0001
19040
validation_fraction
0.284245805161085
19040
verbose
0
19040
warm_start
false
19040
openml-python
Sklearn_1.0.1.
1504
steel-plates-fault
https://www.openml.org/data/download/1592296/php9xWOpn
-1
22096376
description
https://api.openml.org/data/download/22096376/description.xml
-1
22096377
predictions
https://api.openml.org/data/download/22096377/predictions.arff
area_under_roc_curve
0.9987402796462003 [0.99874,0.99874]
average_cost
0
f_measure
0.9922839278632269 [0.994064,0.98893]
kappa
0.9829943992201314
kb_relative_information_score
0.9747807914817902
mean_absolute_error
0.012133876059558771
mean_prior_absolute_error
0.45306405137877787
weighted_recall
0.9922720247295209 [0.990536,0.995542]
number_of_instances
1941 [1268,673]
precision
0.9923425616586922 [0.997617,0.982405]
predictive_accuracy
0.9922720247295209
prior_entropy
0.9311124141243181
relative_absolute_error
0.026781811584107373
root_mean_prior_squared_error
0.47592842871248736
root_mean_squared_error
0.07858323682665014
root_relative_squared_error
0.16511566043499154
total_cost
0
unweighted_recall
0.9930393126497017 [0.990536,0.995542]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
0.9997649547537901 [0.999765,0.999765]
area_under_roc_curve
0.9994123868844753 [0.999412,0.999412]
area_under_roc_curve
0.9984722058996357 [0.998472,0.998472]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
0.9996474321306853 [0.999647,0.999647]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
0.9995299095075801 [0.99953,0.99953]
area_under_roc_curve
0.9921802054154994 [0.99218,0.99218]
area_under_roc_curve
0.9990662931839402 [0.999066,0.999066]
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
f_measure
1 [1,1]
f_measure
0.9948542650470037 [0.996047,0.992593]
f_measure
0.9845627951410111 [0.988142,0.977778]
f_measure
0.9846129815900818 [0.988048,0.978102]
f_measure
1 [1,1]
f_measure
0.9845082688528476 [0.988235,0.977444]
f_measure
0.9897256153320434 [0.992063,0.985294]
f_measure
0.9948542650470037 [0.996047,0.992593]
f_measure
0.9948539051709485 [0.996016,0.992701]
f_measure
0.9948539051709485 [0.996016,0.992701]
kappa
1
kappa
0.9886403560135848
kappa
0.9659210680407543
kappa
0.9661588556808932
kappa
1
kappa
0.965679915084326
kappa
0.9773602520714203
kappa
0.9886403560135848
kappa
0.9887169943003373
kappa
0.9887169943003373
kb_relative_information_score
0.9903497565372484
kb_relative_information_score
0.9789645411347638
kb_relative_information_score
0.965423151997195
kb_relative_information_score
0.9581760441575891
kb_relative_information_score
0.9869736887113961
kb_relative_information_score
0.9668490659800717
kb_relative_information_score
0.963474619572938
kb_relative_information_score
0.9845570594725557
kb_relative_information_score
0.9784254806971094
kb_relative_information_score
0.9744658279588436
mean_absolute_error
0.005033296255428742
mean_absolute_error
0.010473460059424355
mean_absolute_error
0.015131690961165263
mean_absolute_error
0.019950882848380702
mean_absolute_error
0.006445653010195374
mean_absolute_error
0.015359277664387563
mean_absolute_error
0.017876468108256924
mean_absolute_error
0.007359783004294655
mean_absolute_error
0.01081865750365831
mean_absolute_error
0.012926192107221766
mean_prior_absolute_error
0.4536732781714767
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.45422372672718864
mean_prior_absolute_error
0.45422372672718864
number_of_instances
195 [127,68]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [126,68]
number_of_instances
194 [126,68]
precision
1 [1,1]
precision
0.9949211643420254 [1,0.985294]
precision
0.984646779674069 [0.992063,0.970588]
precision
0.98519882179676 [1,0.957143]
precision
1 [1,1]
precision
0.9845385231177758 [0.984375,0.984848]
precision
0.9899895413118183 [1,0.971014]
precision
0.9949211643420254 [1,0.985294]
precision
0.9949200657403257 [1,0.985507]
precision
0.9949200657403257 [1,0.985507]
predictive_accuracy
1
predictive_accuracy
0.9948453608247422
predictive_accuracy
0.9845360824742267
predictive_accuracy
0.9845360824742267
predictive_accuracy
1
predictive_accuracy
0.9845360824742267
predictive_accuracy
0.9896907216494846
predictive_accuracy
0.9948453608247422
predictive_accuracy
0.9948453608247422
predictive_accuracy
0.9948453608247422
prior_entropy
0.932928534004902
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9345694345320188
prior_entropy
0.9345694345320188
relative_absolute_error
0.011094539832090987
relative_absolute_error
0.0231383415975732
relative_absolute_error
0.03342947148524249
relative_absolute_error
0.044076202124206994
relative_absolute_error
0.01423996657485928
relative_absolute_error
0.03393226414901787
relative_absolute_error
0.039493331076846244
relative_absolute_error
0.016259495168852816
relative_absolute_error
0.023817904849686787
relative_absolute_error
0.028457765076163377
root_mean_prior_squared_error
0.4765680392655914
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.4771452028525092
root_mean_prior_squared_error
0.4771452028525092
root_mean_squared_error
0.03769938953948619
root_mean_squared_error
0.06912085080266055
root_mean_squared_error
0.10177262540250724
root_mean_squared_error
0.1025571129312714
root_mean_squared_error
0.04273953670025383
root_mean_squared_error
0.0822208067926866
root_mean_squared_error
0.08972346866004201
root_mean_squared_error
0.07264703928715614
root_mean_squared_error
0.07849601784107055
root_mean_squared_error
0.0814048215002351
root_relative_squared_error
0.07910599627617143
root_relative_squared_error
0.14536816501674807
root_relative_squared_error
0.2140381611612035
root_relative_squared_error
0.21568801805981938
root_relative_squared_error
0.089885583751274
root_relative_squared_error
0.17291870211165528
root_relative_squared_error
0.1886975615402288
root_relative_squared_error
0.1527840973084059
root_relative_squared_error
0.16451180347575353
root_relative_squared_error
0.1706080685996087
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
unweighted_recall
1 [1,1]
unweighted_recall
0.9960629921259843 [0.992126,1]
unweighted_recall
0.9846632976848043 [0.984252,0.985075]
unweighted_recall
0.9881889763779528 [0.976378,1]
unweighted_recall
1 [1,1]
unweighted_recall
0.9811376189916559 [0.992126,0.970149]
unweighted_recall
0.9921259842519685 [0.984252,1]
unweighted_recall
0.9960629921259843 [0.992126,1]
unweighted_recall
0.996031746031746 [0.992063,1]
unweighted_recall
0.996031746031746 [0.992063,1]
usercpu_time_millis
576.5692309978476
usercpu_time_millis
446.60961000045063
usercpu_time_millis
517.3425650009449
usercpu_time_millis
319.5494379997399
usercpu_time_millis
433.20130899883225
usercpu_time_millis
397.21948000078555
usercpu_time_millis
339.1975119993731
usercpu_time_millis
576.4540279997163
usercpu_time_millis
429.68818599911174
usercpu_time_millis
327.8513049990579
usercpu_time_millis_testing
6.899775999045232
usercpu_time_millis_testing
6.289449000178138
usercpu_time_millis_testing
6.924013001480489
usercpu_time_millis_testing
6.614362999243895
usercpu_time_millis_testing
6.66148199888994
usercpu_time_millis_testing
7.179922000432271
usercpu_time_millis_testing
6.4750380006444175
usercpu_time_millis_testing
6.439437000153703
usercpu_time_millis_testing
6.439238999519148
usercpu_time_millis_testing
4.2789489998540375
usercpu_time_millis_training
569.6694549988024
usercpu_time_millis_training
440.3201610002725
usercpu_time_millis_training
510.4185519994644
usercpu_time_millis_training
312.935075000496
usercpu_time_millis_training
426.5398269999423
usercpu_time_millis_training
390.0395580003533
usercpu_time_millis_training
332.7224739987287
usercpu_time_millis_training
570.0145909995626
usercpu_time_millis_training
423.2489469995926
usercpu_time_millis_training
323.57235599920386
wall_clock_time_millis
585.1528644561768
wall_clock_time_millis
449.7549533843994
wall_clock_time_millis
537.6722812652588
wall_clock_time_millis
331.7422866821289
wall_clock_time_millis
445.3320503234863
wall_clock_time_millis
406.97264671325684
wall_clock_time_millis
344.9125289916992
wall_clock_time_millis
596.2982177734375
wall_clock_time_millis
438.24028968811035
wall_clock_time_millis
329.9708366394043
wall_clock_time_millis_testing
6.905078887939453
wall_clock_time_millis_testing
6.296396255493164
wall_clock_time_millis_testing
6.931543350219727
wall_clock_time_millis_testing
12.436628341674805
wall_clock_time_millis_testing
6.667375564575195
wall_clock_time_millis_testing
7.186174392700195
wall_clock_time_millis_testing
6.6089630126953125
wall_clock_time_millis_testing
6.443977355957031
wall_clock_time_millis_testing
8.221626281738281
wall_clock_time_millis_testing
4.283905029296875
wall_clock_time_millis_training
578.2477855682373
wall_clock_time_millis_training
443.45855712890625
wall_clock_time_millis_training
530.7407379150391
wall_clock_time_millis_training
319.3056583404541
wall_clock_time_millis_training
438.66467475891113
wall_clock_time_millis_training
399.78647232055664
wall_clock_time_millis_training
338.3035659790039
wall_clock_time_millis_training
589.8542404174805
wall_clock_time_millis_training
430.01866340637207
wall_clock_time_millis_training
325.6869316101074
weighted_recall
1 [1,1]
weighted_recall
0.9948453608247423 [0.992126,1]
weighted_recall
0.9845360824742269 [0.984252,0.985075]
weighted_recall
0.9845360824742269 [0.976378,1]
weighted_recall
1 [1,1]
weighted_recall
0.9845360824742269 [0.992126,0.970149]
weighted_recall
0.9896907216494846 [0.984252,1]
weighted_recall
0.9948453608247423 [0.992126,1]
weighted_recall
0.9948453608247423 [0.992063,1]
weighted_recall
0.9948453608247423 [0.992063,1]